• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.786-792
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• 2001

In this paper, the identification of connections for a vibration system has been presented using FRF-based substructural sensitivity analysis. The substructural design sensitivity formula is derived and plugged into a commercial optimization program, MATLAB, to identify connection stiffness of an air-conditioner system of passenger car. The air-conditioner system, composed of a compressor and a bracket is analyzed by using FRF-based substructural(FBS) method. To obtain the FRFs, FE model is built for the bracket, and the impact hammer test is performed for the compressor. Obtained FRFs are combined to calculate the reaction force at the connection point and the system response. Connection element properties are determined by minimizing the difference between a target FRF and calculated one. It is shown that the proposed identification method is effective even for a real problem.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.390-395
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• 2000

We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.346-347
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• 2018

This study is a case study on ship zone identification for the generalization of fire safety module in Korean e-Navigation system and assessed the method of dividing the area of the ship based on the location of the fire detector of the target ship.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.579-592
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• 2010

This paper presents a multi-phase model update approach for system identification of prestressed concrete (PSC) girders under various prestress forces. First, a multi-phase model update approach designed on the basis of eigenvalue sensitivity concept is newly proposed. Next, the proposed multi-phase approach is evaluated from controlled experiments on a lab-scale PSC girder for which forced vibration tests are performed for a series of prestress forces. On the PSC girder, a few natural frequencies and mode shapes are experimentally measured for the various prestress forces. The corresponding modal parameters are numerically calculated from a three-dimensional finite element (FE) model which is established for the target PSC girder. Eigenvalue sensitivities are analyzed for potential model-updating parameters of the FE model. Then, structural subsystems are identified phase-by-phase using the proposed model update procedure. Based on model update results, the relationship between prestress forces and model-updating parameters is analyzed to evaluate the influence of prestress forces on structural subsystems.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2693-2706
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• 1999

Reengineering to object-oriented system is needed to maintain the system and satisfy requirements of structure change. Target systems which should be reengineered to object-oriented system are difficult to change because these systems have no design document or their design document is inconsistent of source code. Using design document to identifying objects for these systems is improper. There are several researches which identify objects through procedural source code analysis. In this paper, we propose automatic object identification method based on clustering of VTFG(Variable-Type-Function Graph) which represents relations among variables, types, and functions. VTFG includes relations among variables, types, and functions that may be basis of objects, and weights of these relations. By clustering related variables, types, and functions using their weights, our method overcomes limit of existing researches which identify too big objects or objects excluding many functions. The method proposed in this paper minimizes user's interaction through automatic object identification and make it easy to reenginner procedural system to object-oriented system.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.38 no.4
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• pp.265-275
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• 2005

A prerequisite for deriving the abundance estimates from acoustic surveys for commercially important fish species is the identification of target strength measurements for selected fish species. In relation to these needs, the goal of this study was to construct a data bank for converting the acoustic measurements of target strength to biological estimates of fish length and to simultaneously obtain the target strength-fish length relationship. Laboratory measurements of target strength on 15 commercially important fish species were carried out at five frequencies of 50, 70, 75, 120 and 200 kHz by single and split beam methods under the controlled conditions of the fresh and the sea water tanks with the 389 samples of dead and live fishes. The target strength pattern on individual fish of each species was measured as a function of tilt angle, ranging from $-45^{\circ}$ (head down aspect) to $+45^{\circ}$ (head up aspect) in $0.2^{\circ}$ intervals, and the averaged target strength was estimated by assuming the tilt angle distribution as N $(-5.0^{\circ},\;15.0^{\circ})$. The TS to fish length relationship for each species was independently derived by a least-squares fitting procedure. Also, a linear regression analysis for all species was performed to reduce the data to a set of empirical equations showing the variation of target strength to a fish length, wavelength and fish species. For four of the frequencies (50, 75, 120 and 200 kHz), an empirical model for fish target strength (TS, dB) averaged over the dorsal sapect of 602 fishes of 10 species and which spans the fish length (L, m) to wavelength (\Lambda,\;m)$ ratio between 5 and 73 was derived: $TS=19.44\;Log(L)+0.56\;Log(\Lambda)-30.9,\;(r^2=0.53)$.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.17-21
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• 2007

Drug discovery is a long process with a low rate of successful new therapeutic discovery regardless of the advances in information technologies. Identification of candidate proteins is an essential step for the drug discovery and it usually requires considerable time and efforts in the drug discovery. The drug discovery is not a logical, but a fortuitous process. Nevertheless, considerable amount of information on drugs are accumulated in UniProt, NCBI, or DrugBank. As a result, it has become possible to try to devise new computational methods classifying drug target candidates extracting the common features of known drug target proteins. In this paper, we devise a method for drug target protein classification by using weighted feature summation and Support Vector Machine. According to our evaluation, the method is revealed to show moderate accuracy $85{\sim}90%$. This indicates that if the devised method is used appropriately, it can contribute in reducing the time and cost of the drug discovery process, particularly in identifying new drug target proteins.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.566-572
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• 2021

A methodology for the identification and coordinates estimation of air cavities under urban ground or sandy soil using its natural poles and natural resonant frequencies is presented. The potential of this methodology was analyzed. Simulation models of PEC (Perfect Electric Conductor)s with various shapes and dimensions were developed using an EM (Electromagnetic) simulator. The Cauchy method was applied to the obtained EM scattering response of various objects from EM simulation models. The natural poles of objects corresponding to its instinct characterization were then extracted. Thus, a library of poles can be generated using their natural poles. The generated library of poles provided the possibility of identifying a target by comparing them with the computed natural poles from a target. The simulation models were made assuming that there is an air cavity under urban ground or sandy soil. The response of the desired target was extracted from the electromagnetic wave scattering data from its simulation model. The coordinates of the target were estimated using the time delay of the impulse response (peak of the impulse response) in the time domain. The MP (Matrix Pencil) method was applied to extract the natural poles of a target. Finally, a 0.2-m-diameter spherical air cavity underground could be estimated by comparing both the pole library of the objects and the calculated natural poles and the natural resonant frequency of the target. The computed location (depth) of a target showed an accuracy of approximately 84 to 93%.

• 한국생물공학회:학술대회논문집
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• 2005.04a
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• pp.82-85
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• 2005

Doxorubicin is a highly-valuable anthracycline-family polyketide drug with a very potent anticancer activity, typically produced by a Gram-positive soil bacterium called Streptomyces peucetius. Thanks to the recent development of Streptomyces genomics-based technologies, the random mutagenesis approach for Streptomyces strain improvement has been switched toward the genomics-based technologies including the application of DNA microarray systems. In order to identify and characterize the genomics-driven potential target genes critical for doxorubincin overproduction, three different types of doxorubicin overproducing strains, a dnrI(doxorubicin-specific positive regulatory gene)-overexpressor, a doxA (gene involved in the conversion from daunorubicin to doxorubicin)-overexpressor, and a recursively-mutated industrial strain, were generated and examined their genomic transcription profiles using Streptomyces DNA microarray systems. The DNA microarray results revealed several potential target genes in S. peucetius genome, whose expressions were significantly either up- or down-regulated comparing with the wild-type strain. A systematic understanding of doxorubicin overproduction at the genomic level presented in this research should lead us a rational design of molecular genetic strain improvement strategy.

• Journal of Ocean Engineering and Technology
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• v.34 no.3
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.